Building Efficient Comparative Effectiveness Trials Through Adaptive Designs, Utility Functions, and Accrual Rate Optimization: Finding the Sweet Spot

• Activity Number: 647
• Type: Contributed
• Date/Time: Thursday, August 8, 2013 : 8:30 AM to 10:20 AM
• Sponsor: Biopharmaceutical Section
• Author(s): Byron Gajewski*+ and Scott M. Berry and Mamatha Pasnoor and Mazen Dimachkie and Laura Herbelin and Richard Barohn
• Companies: Univ of Kansas-Medical Center and Berry Consultants and University of Kansas Medical Center and University of Kansas Medical Center and University of Kansas Medical Center and University of Kansas Medical Center
• Keywords: Bayesian adaptive design ; comparative effectiveness ; accrual ; enrollment

Abstract

The time is right for the use of Bayesian Adaptive Designs (BAD) in comparative effectiveness trials. BAD save time and money and lean towards more ethical studies. There are multiple aspects to a BAD that need to be considered when designing a comparative effectiveness design. First, the adaptation rule can determine the expected size of the trial. Second, the utility function can be used to combine extremely important co-endpoints (e.g. combining efficacy and tolerability of a treatment), and is a valuable tool for incorporating clinical expertise and potentially patient opinion. Third, accrual is also very, very important. Specifically, there is a juxtaposition related to accrual and BAD. If accrual is too fast we will never gain information for adapting. If accrual is too slow we will never finish the clinical trial. We propose methodology for finding the "sweet spot" for accrual in relation to BAD that addresses adaptation, utility, and accrual; treating these as design parameters. We will demonstrate the methodology on a comparative effectiveness BAD of pharmaceutical agents in diabetic and cryptogenic sensory polyneuropathy.